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NASA NTRS2015

On the Crack Bifurcation and Fanning of Crack Growth Data

Crack growth data obtained from ASTM load shedding method for different R values show some fanning especially for aluminum alloys. It is believed by the authors and it has been shown before that the observed fanning is due to the crack bifurcation occurs in the near threshold region which is a function of intrinsic properties of the alloy. Therefore, validity of the ASTM load shedding test procedure and results is confirmed. However, this position has been argued by some experimentalists who believe the fanning is an artifact of the test procedure and thus the obtained results are invalid. It has been shown that using a special test procedure such as using compressively pre-cracked specimens will eliminate the fanning effect. Since not using the fanned data fit can result in a significantly lower calculated cyclic life, design of a component, particularly for rotorcraft and propeller systems will considerably be impacted and therefore this study is of paramount importance. In this effort both test procedures i.e. ASTM load shedding and the proposed compressive pre-cracking have been used to study the fatigue crack growth behavior of compact tension specimens made of aluminum alloy 2524-T3. Fatigue crack growth paths have been closely observed using SEM machines to investigate the effects of compression pre-cracking on the crack bifurcation behavior. The results of this study will shed a light on resolving the existing argument by better understanding of near threshold fatigue crack growth behavior.

Forman, Royce G.↗

NASA NTRSDate not supplied

Predicting Melt Properties Using Atomistic Simulations With A Highly Accurate Physically Informed Neural Network Interatomic Potential

The use of a recently developed machine learning (ML) interatomic potential for molecular dynamics simulations of aluminum melt properties will be presented. Such properties are critical for process modeling in additive manufacturing, including the melt pool size, solidification, and formation of solidification microstructures. Direct first-principles modeling of these processes is computationally prohibitive whereas simulations employing ML potentials combine the high accuracy of quantum-mechanical methods with high computational speeds. The physically-informed neural network (PINN) method used herein, integrates a high-dimensional regression implemented by an artificial neural network with a physics-based bond-order interatomic potential. PINN potentials can accurately reproduce many properties of aluminum in both crystalline-solid and liquid phases. We examine the accuracy of a PINN Al potential in predicting the density, self-diffusivity, viscosity, and the tension of the liquid surface and liquid-solid interfaces. Comparison with experimental data and ab initio molecular dynamics calculations shows very good agreement for all properties tested.

molecular dynamics↗

NASA NTRS1992

An interlaminar tension strength specimen

This paper describes a technique to determine interlaminar tension strength, sigma(sub 3c) of a fiber reinforced composite material using a curved beam. The specimen was a unidirectional curved beam, bent 90 degrees, with straight arms. Attached to each arm was a hinged loading mechanism which was held by the grips of a tensile testing machine. Geometry effects of the specimen, including the effects of loading arm length, inner radius, thickness, and width, were studied. The data sets fell into two categories: low strength corresponding to a macroscopic flaw related failure and high strength corresponding to a microscopic flaw related failure. From the data available, the loading arm length had no effect on sigma(sub 3c). The inner radius was not expected to have a significant effect on sigma(sub 3c), but this conclusion could not be confirmed because of differences in laminate quality for each curve geometry. The thicker specimens had the lowest value of sigma(sub 3c) because of poor laminate quality. Width was found to affect the value of sigma(sub 3c) only slightly. The wider specimens generally had a slightly lower strength since more material was under high stress, and hence, had a larger probability of containing a significant flaw.

Jackson, Wade C.↗

NASA NTRS2018

Characterizing Material Scalability for Ultralight Lattice Design

Stiff yet ultra-light lattice structures constructed using digital materials have many practical applications as the building block for aircraft and other structures. By furthering our understanding of how material configuration affects the structural properties of an ultralight lattice, we can intelligently design these structures based on their intended function. Here we compare the behavior of ultralight lattice structures when fabricated by different materials. The individual unit cells of the lattice structures are referred to as voxels. The stiffness, elastic modulus, and yield strength of the specimens in compression and tension are determined through mechanical testing. Specimens are tested both as single voxel as well as 4x4x4 voxel constructions on an Instron 5982 Universal Testing System until failure. Each voxel is manufactured in bulk through injection molding, with a unit cell pitch of 76.2 mm. Individual voxels are fastened with machine screws and nuts to create assemblies. Four separate materials are used as voxel compositions in this experiment. These include a homogeneous polymer referred to as Ultem 1000, a glass-fiber reinforced polymer referred to as Ultem 2200, a polymer with chopped carbon fibers as 30% of its fill, and homogenous polypropylene. This work compares mechanical behavior, as well as the convergence behavior of the lattice as the size of the lattice assembly increases for various materials. The goal of this study is to characterize the behavior of homogenous lattices such that heterogenous lattices can be designed with different material voxels to achieve target material properties for ultralight space applications.

Sajjadi, Afsheen↗

NASA NTRS1994

Design and construction of a tensile tester for the testing of simple composites

The following is a design for a tensile tester which will be used to test the tensile strength and anisotropic properties of simple composites. These simple composites are suspected to be anisotropic primarily in a single plane. When the composites undergo a tensile force, they will undergo deformation, causing movement either to the left or right. The composites are suspect due to their method of construction. Each sample has a single layer of unidirectional continuous fibers embedded in a rubbery resin. It has been well established that a serious limitation of unidirectional fiber composites is the very large in-plane anisotropy. The design presented here incorporates a single degree of freedom such that distortion (to the left or right) due to anisotropic tendencies may be measured. The device will spend the vast majority of its time in an undergraduate materials lab. As a result, ease of use and durability are valued more highly than research grade accuracy. Additional concerns focus on the fact that this machine will be built as a student project. Issues which are dealt with during this design include: specimen configuration or shape; a method of applying consistent, linear tension force; a method of gripping specimen without affecting its overall properties; a method of collecting data; repeatability of data; ease of use; ease of construction; and cost. After the device has been constructed, it will be used to test the simple composites which were fabricated in house. A comparison will be made between composites manufactured using aluminum screening as the strengthening fibers and those manufactured using fiberglass screening.

Borst, Mark A.↗

DOE OSTI2022

Quasi-static to Dynamic Response and Microstructure Development of Tantalum-Tungsten Alloys

Lawrence Livermore National Laboratory (LLNL) has a need to understand the quasi-static to dynamic mechanical response and microstructure evolution of tantalum-tungsten (Ta-W) alloys made by conventional wrought processing and additive manufacturing (AM). This two-year work scope will be performed at the Colorado School of Mines (Mines) and will include quasi-static (e.g., 10 -3 s -1 ) mechanical testing in tension and compression, along with high strain rate (Kolsky) pressure bar testing in tension and compression (e.g., 10 3 s -1 ), without and with temperature variations. Gas gun experiments at higher strain rates (e.g., over 10 3 s -1 ) will also be pursued. Complementary microstructure characterization will be performed on undeformed and deformed samples to fundamentally understand the role of processing on the microstructure characteristics and resulting deformation mechanisms that dictate the mechanical response of these alloys with variations in strain rate, temperature, and strain state. Alloys of interest will be Ta-based, containing up to 10 wt.% W. LLNL will supply initial wrought-processed material for sample machining. LLNL will also supply samples built by AM during the project for testing. Arc melting and casting may also be performed at Mines to produce small quantities of different alloys for machining and exploratory testing on an as-needed basis. This project will support multiple postdocs and graduate students at Mines, training them with the knowledge, skills, and abilities needed to study materials under extreme conditions of interest to the National Nuclear Security Agency.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Computational catalyst discovery: Active classification through myopic multiscale sampling

We report the recent boom in computational chemistry has enabled several projects aimed at discovering useful materials or catalysts. We acknowledge and address two recurring issues in the field of computational catalyst discovery. First, calculating macro-scale catalyst properties is not straightforward when using ensembles of atomic-scale calculations [e.g., density functional theory (DFT)]. We attempt to address this issue by creating a multi-scale model that estimates bulk catalyst activity using adsorption energy predictions from both DFT and machine learning models. The second issue is that many catalyst discovery efforts seek to optimize catalyst properties, but optimization is an inherently exploitative objective that is in tension with the explorative nature of early-stage discovery projects. In other words, why invest so much time finding a “best” catalyst when it is likely to fail for some other, unforeseen problem? We address this issue by relaxing the catalyst discovery goal into a classification problem: “What is the set of catalysts that is worth testing experimentally?” Here, we present a catalyst discovery method called myopic multiscale sampling, which combines multiscale modeling with automated selection of DFT calculations. It is an active classification strategy that seeks to classify catalysts as “worth investigating” or “not worth investigating” experimentally. Our results show an ~7–16 times speedup in catalyst classification relative to random sampling. These results were based on offline simulations of our algorithm on two different datasets: a larger, synthesized dataset and a smaller, real dataset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2002

Influence of Crack-Tip Configurations on the Fracture Response of 0.04-Inch Thick 2024-T3 Aluminum Alloy Sheet

A series of fracture tests were conducted on Middle-crack tension M(T) and compact tension C(T) specimens to determine the effects of specimen type, specimen width, notch tip sharpness and buckling on the fracture behavior of cracked thin sheet (0.04 inch thick) 2024-T3 aluminum alloy material. A series of M(T) specimens were tested with three notch tip configurations: (1) a fatigue pre-cracked notch, (2) a 0.010-inch-diameter wire electrical discharge machined (EDM) notch, and (3) a EDM notch sharpened with a razor blade. The test procedures are discussed and the experimental results for failure stress, load vs. crack extension and the material stress-strain response are reported.

Johnston, William M.↗

DOE OSTI2021

Testing in Support of the Development of EPP Plus SMT Design Method at ORNL (FY2021)

Experiments in support of the development of the integrated Elastic–Perfectly Plastic (EPP) plus Simplified Model Test (SMT) design methodology, referred to as the EPP+SMT method, continued in FY21. This report focuses on the methodology for developing the EPP+SMT creep-fatigue (CF) design curves at low strain ranges. The creep damage-based method and dissipated work-based method were used to evaluate the available CF data at the low strain range region. A set of failure criteria were determined, and a simple extrapolation method was developed to predict the CF life cycles at low strain ranges that are not accessible by experiments due to the extraordinarily long failure times at the low strain region (thousands to hundreds of thousands of years) and the inability of the test machine to control these small strain ranges due to the signal to noise issues. An experimental method with the concept of block-strain range CF testing was proposed to generate the information needed to extrapolate the CF design curves to low strain ranges. Based on this new testing approach, a preliminary EPP+SMT CF design curve was developed for Alloy 617 at 950°C with tension hold time of 100 s. The analysis in this report shows the potential of generating a set of EPP+SMT CF design curves with different hold times within a reasonable amount of time and testing effort. Based on such a progress, a hold time extrapolation procedure for low strain ranges will be developed in FY22 and critical testing will be carried out to complete the development of the EPP+SMT CF design curves for Alloy 617.

36 MATERIALS SCIENCE↗

NASA NTRS1980

Measurements of mixed-mode crack surface displacements and comparison with theory

The problem of a finite-width tension specimen containing a crack oriented at various angles to the load axis is attacked from experimental and theoretical viewpoints. Displacements of an electro-machined slot, 12.5 mm long and oriented at angles of 0, 15, 30, 45, 60, and 75 deg, are measured using a laser-based in-plane measuring technique. Various width specimens, ranging from a crack-length/width ratio of 0.167 to 0.794, are tested. A boundary-integral equation method is extended to deal with the presence of a sharp crack. Agreement between the two approaches is generally good except near the tips of the cracks.

Sharpe, W. N., Jr.↗

NASA NTRS1999

Influence of Specimen Preparation and Specimen Size on the Transverse Tensile Strength and Scatter of Glass Epoxy Laminates

The influence of specimen polishing, specimen configuration, and specimen size on the transverse tension strength of two glass epoxy materials loaded in three and four point bending was evaluated. Polishing machined edges, and/or tension side failure surfaces, was detrimental to specimen strength characterization instead of yielding a higher, more accurate, strength as a result of removing inherent manufacture and handling flaws. Transverse tension strength was sensitive to span length due to the classical weakest link effect. However, strength was less sensitive to volume changes achieved by increasing specimen width. The Weibull scaling law over-predicted changes in transverse tension strengths in three point bend tests and under-predicted changes in transverse tension strengths in four point bend tests. Furthermore, the Weibull slope varied with specimen configuration, volume, and sample size. Hence, the utility of this scaling law for predicting transverse tension strength is unclear.

OBrien, T. Kevin↗

DOE OSTI2024

Machine Learning for Joint Quality Control

The use of lightweight material combinations has been highly demanded in manufacturing automotive structures. However, making robust dissimilar material joints of such lightweight materials is still challenging. A significant barrier to achieving high-quality and repeatable joint performance is a deficient understanding of the relationship between the welding process, joint attributes, and joint performance. In this context, welding factors refer to material, equipment, environment, and process parameters, while joint features comprise specific microstructural attributes of the weld such as nugget size, heat affected zone (HAZ) topology, intermetallic layer thickness, and sheet thickness reduction. Joint performance is quantified in terms of strength (e.g., tensile shear, coach peel, cross-tension), weld size, and hardness, among other factors. While there have been many attempts to establish this process-structure-property relationship by developing a model derived from the associated physics and first principles, the complexity of the joining processes compounded by the complex interactions with different materials in an automotive assembly line environment, has hindered the usefulness of such attempts. The complexity is further exacerbated using different stacking materials, especially comprising dissimilar material combinations. In practice, the common approach has been the laborious process of creating welds, characterizing them, and then physically testing them through experimentation. With the emergence of artificial intelligence (AI) methods, an alternative pathway to eliciting the desired process-structure-property relationship at an accelerated pace is to use a data-driven approach by employing machine-learning (ML) techniques. This approach is benefitted by the availability of large streams of data, generated through years of research and testing by original equipment manufacturers, in the form of material, process, environmental, equipment, microstructural, and bulk-scale performance information from multimodal, multiscale sensors making measurements from laboratory-scale to production-scale processes. During Phase I efforts, which ended in fiscal year (FY) 2021, the Oak Ridge National Laboratory and Pacific Northwest National Laboratory (ORNL/PNNL) team demonstrated the effectiveness of different ML/AI frameworks in modeling complex relationships between resistance spot welding (RSW) process parameters, weld attributes, and joint properties using a subset of data from General Motors (GM). In FY 2022, the project team further refined and expanded their respective ML models to analyze additional welds with new weld stack-ups and materials to enhance the ML model predictive capability. ORNL extended its unified deep neural networks (DNN) ML training and prediction framework with new data streams of process parameters, and PNNL extended its model describing RSW process parameters’ associations with weld attributes. In FY 2023, the project team completed the development of the AI/ML architecture for analyzing aluminum/steel joints manufactured by GM via RSW and transitioned into the inline welding quality monitoring task for steel/steel RSW joints provided by GM.

36 MATERIALS SCIENCE↗

NASA NTRS2001

Influence of Specimen Preparation and Specimen Size on Composite Transverse Tensile Strength and Scatter

The influence of specimen polishing, configuration, and size on the transverse tension strength of two glass-epoxy materials, and one carbon-epoxy material, loaded in three and four point bending was evaluated. Polishing machined edges, arid/or tension side failure surfaces, was detrimental to specimen strength characterization instead of yielding a higher, more accurate, strength as a result of removing inherent manufacture and handling flaws. Transverse tension strength was typically lower for longer span lengths due to the classical weakest link effect. However, strength was less sensitive to volume changes achieved by increasing specimen width. The Weibull scaling law typically over-predicted changes in transverse tension strengths in three point bend tests and under-predicted changes in transverse tension strengths in four point bend tests. Furthermore, the Weibull slope varied with specimen configuration, volume, and sample size. Hence, this scaling law was not adequate for predicting transverse tension strength of heterogeneous, fiber-reinforced, polymer matrix composites.

OBrien, T. Kevin↗

DOE OSTI2023

Evaluation of the ring tension test (RTT) for robust determination of material strengths

The ring tension test (RTT) is an experimental method for determining mechanical behavior in a material’s circumferential or hoop direction. It is a crucial test for testing anisotropic materials with tube geometry, such as nuclear fuel cladding or irradiated pipes. Several RTT configurations exist, each with their own advantages and disadvantages. However, this test is significantly more complex than traditional tensile testing and can be especially sensitive to small differences and inconsistencies in the test setup and geometry, ultimately affecting the derived mechanical properties. Previous research has focused on method development, and little work has been done on understanding the subtle differences between an ideal test and experiments, specifically when the tests are performed on highly irradiated materials in hot cells. In this work, a finite element-based investigation of the RTT is conducted to fill this gap. The two most used test configurations are investigated, comparing their ability to determine accurate material strengths through plastic deformation. Several non-ideal conditions and uncontrollable effects which are likely to occur during experimental testing such as machining tolerances, variations of specimen geometry from nominal dimensions, rotation of specimens and fixturing, and other test setup discrepancies are studied. The sensitivity of measured strengths to these conditions is presented. A mechanics-based approach to describing and correcting raw data to determine actual strengths is also included for one of the configurations, resulting in a robust correction method with highly accurate material strength measurements. Finally, based on these analyses, the hemicylindrical mandrel configuration is recommended with a gauge region oriented at a 45° angle.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Findings on Subtask 3.1 - Bakken Rich Gas Enhanced Oil Recovery Project

Total in-place oil for the Bakken petroleum system (BPS) (which includes the Bakken and Three Forks Formations) has been estimated to be 600 billion barrels (bbl). However, BPS wells have decline rates as high as 85% over the first 3 years of their lives, and primary recovery factors typically range from 3% to 10% of original oil in place. Given the low initial recovery rates, even small incremental productivity improvements could dramatically increase technically recoverable oil in the BPS. One potential solution is enhanced oil recovery (EOR) using gas injection, such as carbon dioxide (CO2) or hydrocarbon (HC) gases. While commonly used in conventional reservoirs, CO2 EOR in unconventional tight oil reservoirs has been limited to pilot tests. EOR using rich gas (mixture of methane, ethane, and propane) has also been employed in numerous pilots in several unconventional plays and has recently been successfully applied in the Eagle Ford play. If successful, large-scale gas-based EOR in the BPS could dramatically increase oil productivity and recovery factors and extend the life of the play for decades. While CO2 may be a technically suitable working fluid for EOR in the BPS, supplies are limited and costs for using CO2 in EOR pilots are prohibitively high. Meanwhile, produced gas flaring has presented challenges for BPS operators in North Dakota. Analysis conducted by the North Dakota Pipeline Authority indicates that the current gas-gathering infrastructure in North Dakota is insufficient to accommodate all of the associated gas that is produced from the BPS. The geographically isolated location of North Dakota relative to large natural gas markets, combined with suppressed natural gas prices, has made it economically challenging for industry to invest capital in expanding gas-gathering infrastructure in the state. These circumstances led to a research program conducted by the Energy & Environmental Research Center (EERC) in partnership with Liberty Resources Management Company LLC (LR) to examine the potential to use rich gas injection for EOR and mitigate flaring. A rich gas EOR pilot test was designed and executed by LR at its Stomping Horse development area in Williams County, North Dakota. From July 2018 through May 2019, a total of 160 million standard cubic feet (MMscf) of rich produced gas was injected into the BPS using five different wells in a sequential injection strategy. LR’s Leon–Gohrick drill spacing unit (DSU) was used as the test site. Regulatory oversight was provided by the North Dakota Industrial Commission (NDIC). Technical support was provided by the EERC through a series of laboratory, modeling, and field-based activities, and additional post-pilot research activities incorporated learnings from the test, developed new laboratory data, improved fracture modeling methods, and developed machine learning and big data analytics. The results from the Stomping Horse rich gas EOR pilot activities indicate that developing an effective, economical EOR approach for the BPS will require more field tests. Another key lesson learned from the Stomping Horse tests is that detailed pre- and posttest data on reservoir conditions and fluids production are essential. Robust reservoir characterization provides information that is crucial to creating realistic geomodels and conducting valid dynamic simulations of potential EOR scenarios. A detailed understanding of the completions and production history of offset wells is also necessary for valid test result interpretations. This knowledge is essential to designing the operational parameters of injectivity tests and interpreting the results. A conformance control strategy is also essential to success. Laboratory-based examinations of rich gas interactions with reservoir fluids and rocks were conducted, with an emphasis on determining the ability to mobilize oil in the tight reservoir rocks and shales of the BPS. Injection fluid composition was shown to have a positive impact on reducing reservoir oil minimum miscibility pressure (MMP), reducing interfacial tension (IFT), and altering wettability. IFT and contact angle measurements demonstrated that wettability can be altered in the presence of rich gas, suggesting the potential to improve oil recovery. Iterative modeling of surface infrastructure and reservoir performance using data generated by the various project activities was conducted. A geologic model of the Stomping Horse area was built; history-matched oil, gas, and water production was used in simulations of various EOR scenarios. Early programmatic modeling results were used to support LR’s design and operation of the EOR pilot and to provide insight regarding optimization of future commercial-scale BPS EOR design and operations. Post-pilot modeling focused on alternative methods of understanding complex fracture networks and accelerating simulation time. These led to improved simulation run times and provide excellent history-matching results. Several of these iterative models were used as the bases for developing algorithms into machine learning and big data analytics. History matching in reservoir simulation is time-consuming and computer processing-intensive. Machine learning algorithms were created, and an automated history-matching tool was developed. A large set of synthetic reservoir simulations were created to generate well responses (oil, gas, and water production, well bottomhole pressure [BHP], and tracer or propane breakthrough) for a set of EOR operating parameters that included offset well status (open or closed), injectate (rich gas or propane), injection rate, and injection well BHP. A user interface was developed to provide real-time visualization. Machine learning-based models were developed to provide rapid forecasting of well performance given a set of user-defined EOR operating parameters. These predictive models allow the user to modify the offset well status, injection rate, and injection well BHP and rapidly forecast future production performance. The combination of real-time visualization tools with real-time forecasting tools provides a framework for real-time control—operational changes that the EOR site operator can enact (e.g., changing gas injection rates) to affect the observed performance and potentially improve the EOR outcome. There is great reason to be optimistic about the future of EOR in the Bakken. The results of the laboratory studies suggest significant potential for high rates of oil mobilization using produced field gas injection under the right conditions. The results of the lab studies, combined with rigorous statistical analysis of well production data and associated modeling efforts, confirm the notion that fluid mobility within the reservoir is controlled by fractures. As more knowledge is gained about the nature and distribution of fracture networks in the Bakken, the industry will be in a better position to predict and, ultimately, influence fluid mobility. New field tests are necessary to develop a more complete understanding of those conditions. Thoughtful and creatively engineered field tests within a well-characterized geologic setting will yield the fundamental knowledge needed to take Bakken oil production to the next level. This subtask was cofunded through the EERC–U.S. Department of Energy Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by the North Dakota Industrial Commission’s Oil and Gas Research Program and Computer Modelling Group.

04 OIL SHALES AND TAR SANDS↗

NASA NTRS1991

Compression, bend, and tension studies on forged Al67Ti25Cr8 and Al66Ti25Mn(g) L1(2) compounds

Cast, homogenized, and isothermally forged aluminum-rich L1(2) compounds Al67Ti25Cr8 and Al66Ti25Mn(g) were tested in compression as a function of temperature and as a function of strain rate at elevated temperatures (1000 K and 1100 K). Three-point bend specimens were tested as a function of temperature in the range 300 K to 873 K. Strain gages glued on the tensile side of the ambient and 473 K specimens enabled direct strain measurements. A number of 'buttonhead' tensile specimens were electro-discharge machined, fine polished, and tested between ambient and 1073 K for yield strength and ductility as a function of temperature. Scanning electron microscope (SEM) examination of fracture surfaces from both the bend and tensile specimens revealed a gradual transition from transgranular cleavage to intergranular failure with increasing temperature.

Kumar, K. S.↗

NASA NTRSDate not supplied

Space Suit Portable Life Support System Thermal Control Valve Ball Design

A Thermal Control Valve (TCV) has been in development for the Exploration Extravehicular Mobility Unit Portable Life Support System (xEMU PLSS). The xEMU PLSS TCV controls flow going to the liquid cooling and ventilation garment that the crew member wears during extra-vehicular activity to expel waste heat. A previous TCV version with a linear actuator and diverter valve has been tested to attempt to control the flow accurately. The previous valve has a non-linear flow response relative to valve position and has struggled to meet the setpoints desired for precise thermal control. While many diverter valve design variations have been attempted, all previous designs have had difficulty meeting set points. Additionally, high precision machining is required to create a metal-on-metal seal which has its own drawbacks and does not always meet requirements for internal leakage. This metal seal also requires stalling a linear actuator to load the seal in compression or tension which has caused sticking failures when stalled. A new approach and design for a TCV has been developed which uses a rotational ball to control flow and has demonstrated a much more precise and linear flow control. The design functions like a two-way ball valve with two Teflon seats that cradle and compress the ball for sealing. The ball outlet has a unique geometric design to create a set-able orifice like hole which is more predictable at controlling flow. Additionally, the Teflon seat performs much better for preventing internal leakage than the metal seal and prevents sticking by having a large range in which it is sealed without having to stall the actuator. This paper will review a new proposed xEMU PLSS TCV ball design and compare it with previous iterations of the design.

Ryan Ogilvie↗

NASA NTRSDate not supplied

Space Suit Portable Life Support System Thermal Control Valve Ball Design

Ryan Ogilvie↗